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# "Newbie: clustering with k-means and then using multipe regression linear"

Member Posts: 3 Contributor I
edited May 2019 in Help
Hi, I'm a student from Indonesia.

Currently I'm working on my assignment to predict lead time manufacturing on make to order manufacture. The dependent attribute is lead time (continuous). and the independent variable are routing, material, etc.

I'm going to use clustering (k-means) to make a few groups of data. and then I will make rules of each group using multiple regression linear.

I'm very new to this software. So the first question is, Can I do these method with Rapid Miner? Then how can I accomplished it? try with simple and detail step please... thank you so much for the attention. and I really hope you can help me.

best regards,
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RapidMiner Certified Analyst, RapidMiner Certified Expert, Member Posts: 2,531 Unicorn
Hi,
for getting more familiar with the software, I really recommend to do the online tutorial available in the welcome screen.
If you have a basic understanding of the software, here is it, how it works for your assignment. But because I'm not getting paid for solving your exercises, I must hold this quite short, but you will get an idea how to work this out.

Here's a process setup, which will first load data (in this case it will be generated randomly). Then KMeans is used as clustering algorithm, which will assign each example to a cluster. This cluster attribute is then used as label, hence the target variable for a following linear regression. You might exchange operator with an analog operator, for example use LinearDiscriminantAnalysis instead of linear regression, or use another clustering operator.
`<operator name="Root" class="Process" expanded="yes">    <operator name="ExampleSetGenerator" class="ExampleSetGenerator">        <parameter key="target_function"	value="spiral cluster"/>        <parameter key="number_of_attributes"	value="2"/>    </operator>    <operator name="KMeans" class="KMeans">    </operator>    <operator name="ChangeAttributeRole" class="ChangeAttributeRole">        <parameter key="name"	value="cluster"/>        <parameter key="target_role"	value="label"/>    </operator>    <operator name="LinearRegression" class="LinearRegression">    </operator></operator>`
I hope that this will help you, solving your problem.

Greetings,
Sebastian
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Member Posts: 3 Contributor I
thank you sebastian,

i really appreciate it.
I've read the tutorial but its getting me dizzy cos english is not my main language. but i'm still good tough hahaha.
so, i can build a model which is clustering the data and then i made a rule on each cluster data set?
thanks again.

nawaf, Indonesia.
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Member Posts: 3 Contributor I
Oh my god...

it works... wow great! thanks a lot pal.